PyTCI 0.1

A package for target controlled infusions

PyTCI

A python package for Target Controlled Infusions.

Spawned from the NHS Hack Day project https://github.com/JMathiszig-Lee/Propofol, this splits out useful code into a package and updates it to python3

Installation

if using pip

pip install PyTCI

if using pipenv (you should, it's great)

pipenv install PyTCI

Usage

PyTCI currently supports the following:

Body Mass equations:

• BMI
• Ideal body weight (Devine)
• Adjusted body weight
• James Equation
• Boer
• Hume(1966)
• Hume(1971)
• Janmahasation(2005)

example:

>>> from PyTCI.weights import leanbodymass
>>> leanbodymass.hume66(180, 60 'm')
51.2

Propofol models:

• Schnider
• Marsh
• Kataria
• Paedfusor

Remifentanil models

• Minto

example:

>>> from PyTCI.models import propofol
>>> patient = propofol.Schnider(40, 70, 170, 'm')
>>> patient.v2
24

the class methods give_drug and wait_time can he used to model propofol kinetics

example:

>>> from PyTCI.models import propofol
>>> patient = propofol.Marsh(90)
>>> patient.give_drug(200)
>>> patient.x1
7.9573934837092715
>>> patient.wait_time(60)
>>> patient.x1
6.179147869674185

The built in models inherit from a parent class. You can define your own models and use the same functions to see how yours performs

class MyNewModel(Propofol):
     def __init__(self, desired, arguments):
        #my custom code to generate volumes and constants
        self.v1 = a_constant * weight
        self.v2 = a_constant * lean_body_mass
        etc... etc...

        #if you want to work with clearances rate constants must be generated
        Propofol.from_clearances(self)

        #finally set up model 
        Propofol.setup(self)